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cs.CL2026
Hint Tuning: Less Data Makes Better Reasoners
Siqi Fan, Minghao Li, Xiaoqian Ma +6
Large reasoning models achieve high accuracy through extended chain-of-thought but generate 5--8 more tokens than necessary, applying verbose reasoning uniformly regardless of prob…
cs.CL2026
Pair-In, Pair-Out: Latent Multi-Token Prediction for Efficient LLMs
Wenhui Tan, Minghao Li, Xiaoqian Ma +5
Long chain-of-thought reasoning has made autoregressive decoding the dominant inference cost of modern large language models. Existing methods target either the input side (latent…
cs.CL2026
Relax: An Asynchronous Reinforcement Learning Engine for Omni-Modal Post-Training at Scale
Liujie Zhang, Benzhe Ning, Rui Yang +8
Reinforcement learning (RL) post-training has proven effective at unlocking reasoning, self-reflection, and tool-use capabilities in large language models. As models extend to omni…